Articles | Volume 12, issue 5
Ocean Sci., 12, 1137–1153, 2016
https://doi.org/10.5194/os-12-1137-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue: REP14-MED: A Glider Fleet Experiment in a Limited Marine...
Ocean Sci., 12, 1137–1153, 2016
https://doi.org/10.5194/os-12-1137-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article 14 Oct 2016
Research article | 14 Oct 2016
A hybrid variational-ensemble data assimilation scheme with systematic error correction for limited-area ocean models
Paolo Oddo et al.
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Cited
11 citations as recorded by crossref.
- A new stochastic ocean physics package and its application to hybrid‐covariance data assimilation A. Storto & P. Andriopoulos 10.1002/qj.3990
- Optimal Assimilation of Daytime SST Retrievals from SEVIRI in a Regional Ocean Prediction System A. Storto & P. Oddo 10.3390/rs11232776
- Assessing the Impact of Different Ocean Analysis Schemes on Oceanic and Underwater Acoustic Predictions A. Storto et al. 10.1029/2019JC015636
- Introducing Along-Track Error Correlations for Altimetry Data in a Regional Ocean Prediction System A. Storto et al. 10.1175/JTECH-D-18-0213.1
- High-resolution observations in the western Mediterranean Sea: the REP14-MED experiment R. Onken et al. 10.5194/os-14-321-2018
- Generating atmospheric forcing perturbations for an ocean data assimilation ensemble I. Mirouze & A. Storto 10.1080/16000870.2019.1624459
- Forecast skill score assessment of a relocatable ocean prediction system, using a simplified objective analysis method R. Onken 10.5194/os-13-925-2017
- The added value of the multi-system spread information for ocean heat content and steric sea level investigations in the CMEMS GREP ensemble reanalysis product A. Storto et al. 10.1007/s00382-018-4585-5
- Extending an oceanographic variational scheme to allow for affordable hybrid and four-dimensional data assimilation A. Storto et al. 10.1016/j.ocemod.2018.06.005
- Synthesis of Ocean Observations Using Data Assimilation for Operational, Real-Time and Reanalysis Systems: A More Complete Picture of the State of the Ocean A. Moore et al. 10.3389/fmars.2019.00090
- An Analytical Four‐Dimensional Ensemble‐Variational Data Assimilation Scheme K. Liang et al. 10.1029/2020MS002314
11 citations as recorded by crossref.
- A new stochastic ocean physics package and its application to hybrid‐covariance data assimilation A. Storto & P. Andriopoulos 10.1002/qj.3990
- Optimal Assimilation of Daytime SST Retrievals from SEVIRI in a Regional Ocean Prediction System A. Storto & P. Oddo 10.3390/rs11232776
- Assessing the Impact of Different Ocean Analysis Schemes on Oceanic and Underwater Acoustic Predictions A. Storto et al. 10.1029/2019JC015636
- Introducing Along-Track Error Correlations for Altimetry Data in a Regional Ocean Prediction System A. Storto et al. 10.1175/JTECH-D-18-0213.1
- High-resolution observations in the western Mediterranean Sea: the REP14-MED experiment R. Onken et al. 10.5194/os-14-321-2018
- Generating atmospheric forcing perturbations for an ocean data assimilation ensemble I. Mirouze & A. Storto 10.1080/16000870.2019.1624459
- Forecast skill score assessment of a relocatable ocean prediction system, using a simplified objective analysis method R. Onken 10.5194/os-13-925-2017
- The added value of the multi-system spread information for ocean heat content and steric sea level investigations in the CMEMS GREP ensemble reanalysis product A. Storto et al. 10.1007/s00382-018-4585-5
- Extending an oceanographic variational scheme to allow for affordable hybrid and four-dimensional data assimilation A. Storto et al. 10.1016/j.ocemod.2018.06.005
- Synthesis of Ocean Observations Using Data Assimilation for Operational, Real-Time and Reanalysis Systems: A More Complete Picture of the State of the Ocean A. Moore et al. 10.3389/fmars.2019.00090
- An Analytical Four‐Dimensional Ensemble‐Variational Data Assimilation Scheme K. Liang et al. 10.1029/2020MS002314
Latest update: 16 Jun 2021
